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  • Title: Sequential binary gene ratio tests define a novel molecular diagnostic strategy for malignant pleural mesothelioma.
    Author: De Rienzo A, Richards WG, Yeap BY, Coleman MH, Sugarbaker PE, Chirieac LR, Wang YE, Quackenbush J, Jensen RV, Bueno R.
    Journal: Clin Cancer Res; 2013 May 01; 19(9):2493-502. PubMed ID: 23493352.
    Abstract:
    PURPOSE: To develop a standardized approach for molecular diagnostics, we used the gene expression ratio bioinformatic technique to design a molecular signature to diagnose malignant pleural mesothelioma (MPM) from among other potentially confounding diagnoses and differentiate the epithelioid from the sarcomatoid histologic subtype of MPM. In addition, we searched for pathways relevant in MPM in comparison with other related cancers to identify unique molecular features in MPM. EXPERIMENTAL DESIGN: We conducted microarray analysis on 113 specimens including MPMs and a spectrum of tumors and benign tissues comprising the differential diagnosis of MPM. We generated a sequential combination of binary gene expression ratio tests able to discriminate MPM from other thoracic malignancies. We compared this method with other bioinformatic tools and validated this signature in an independent set of 170 samples. Functional enrichment analysis was conducted to identify differentially expressed probes. RESULTS: A sequential combination of gene expression ratio tests was the best molecular approach to distinguish MPM from all the other samples. Bioinformatic and molecular validations showed that the sequential gene ratio tests were able to identify the MPM samples with high sensitivity and specificity. In addition, the gene ratio technique was able to differentiate the epithelioid from the sarcomatoid type of MPM. Novel genes and pathways specifically activated in MPM were identified. CONCLUSIONS: New clinically relevant molecular tests have been generated using a small number of genes to accurately distinguish MPMs from other thoracic samples, supporting our hypothesis that the gene expression ratio approach could be a useful tool in the differential diagnosis of cancers.
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